Llovet, J. M. | bioRxiv Science

bioRxiv2025

Molecular insights into early malignant transition of hepatocellular carcinoma

The molecular continuum of premalignant-to-malignant transition remains elusive in carcinogenesis, primarily due to the difficulty in sampling transitional lesions. Here, we present comprehensive genomic and immunological profiling of 21 very early hepatocellular carcinomas (veHCCs) arising within 17 cancer-prone DNs. Surprisingly, 82% of cancer-prone DNs harbored TERT alterations, suggesting a predisposing rather than causative role in malignancy transition. A substantial increase in CNA burden, rather than SNV, was noted, indicating a role of chromosome instability in malignancy transition. Additionally, veHCC-originating DNs showed immune inactivity, not falling into the prevailing paradigm that HCCs develop in a context of chronic inflammation. 43% of veHCCs showed an inflamed phenotype with relatively mild CNA burden but already exhibited immune evasion features. Two major evolutionary scenarios were thus proposed: 1) CNA-dominant progression and 2) early immune evasion of those with mild CNA burden. Collectively, our findings illustrate previously unexplored molecular paradigms in HCC initiation, highlighting the therapeutic potential of immunotherapy for early intervention.

cancer biology↗

bioRxiv2022

CXCR2 inhibition enables NASH-HCC immunotherapy

ObjectiveHepatocellular carcinoma (HCC) is increasingly associated with non-alcoholic steatohepatitis (NASH). HCC immunotherapy offers great promise; however, recent data suggests NASH-HCC may be less sensitive to conventional immune checkpoint inhibition (ICI). We hypothesised that targeting neutrophils using a CXCR2 small molecule inhibitor may sensitise NASH-HCC to ICI therapy. DesignNeutrophil infiltration was characterised in human HCC and mouse models of HCC. Late-stage intervention with anti-PD1 and/or a CXCR2 inhibitor was performed in murine models of NASH-HCC. The tumour immune microenvironment was characterised by imaging mass cytometry, RNA-seq and flow cytometry. ResultsNeutrophils expressing CXCR2, a receptor crucial to neutrophil recruitment in acute-injury, are highly represented in human NASH-HCC. In models of NASH-HCC lacking response to ICI, the combination of a CXCR2 antagonist with anti-PD1 suppressed tumour burden and extended survival. Combination therapy increased intratumoral XCR1+ dendritic cell activation and CD8+ T cell numbers which are associated with anti-tumoral immunity, this was confirmed by loss of therapeutic effect upon genetic impairment of myeloid cell recruitment, neutralisation of the XCR1-ligand XCL1 or depletion of CD8+ T cells. Therapeutic benefit was accompanied by an unexpected increase in tumour-associated neutrophils (TANs) which switched from a pro-tumor to anti-tumour progenitor-like neutrophil phenotype. Reprogrammed TANs were found in direct contact with CD8+ T cells in clusters that were enriched for the cytotoxic anti-tumoural protease granzyme B. Neutrophil reprogramming was not observed in the circulation indicative of the combination therapy selectively influencing TANs. ConclusionCXCR2-inhibition induces reprogramming of the tumour immune microenvironment that promotes ICI in NASH-HCC. Significance of this studyWhat is already known on this subject? O_LIImmune checkpoint inhibition therapy is emerging as a promising new therapy for the treatment of advanced hepatocellular carcinoma (HCC). C_LIO_LIOnly a minority of HCC patients will respond to immune checkpoint inhibition (ICI) therapy and recent data suggest that HCC on the background of NASH may have reduced sensitivity to this treatment strategy. C_LIO_LINeutrophils are a typical myeloid component of the liver in NASH and are found either within the HCC tumour microenvironment or in a peritumoural location. C_LIO_LINeutrophils have considerable phenotypic plasticity and can exist in both tumour promoting and tumour suppressing states. C_LIO_LINeutrophils may have the ability to influence ICI therapy. C_LI What are the new findings? O_LICXCR2+ neutrophils are found in human NASH and within the tumour of both human and mouse models of NASH-HCC. C_LIO_LIThe resistance of NASH-HCC to anti-PD1 therapy is overcome by co-treatment with a CXCR2 small molecule inhibitor, with evidence of reduced tumour burden and extended survival. C_LIO_LIAnti-PD1 and CXCR2 inhibitor combine to selectively reprogramme tumour-associated neutrophils (TANs) from a pro- to an anti-tumour phenotype. C_LIO_LIReprogrammed TANs proliferate locally within Granzyme B+ immune clusters that contain physically associating CD8+ T cells and antigen presenting cells. C_LIO_LIConventional XCR1+ dendritic cells (cDC1s) are found to be elevated in anti-PD1 and CXCR2 inhibitor treated HCCs and together with CD8+ T cells are required for therapeutic benefit. C_LI How might it impact on clinical practice in the foreseeable future? O_LITANs can be selectively manipulated to adopt an anti-tumour phenotype which unlocks their potential for cancer therapy. The ability of CXCR2 antagonism to combine with ICI therapy to bring about enhanced therapeutic benefit in NASH-HCC (and potentially in HCC of other aetiologies) warrents clinical investigation. C_LI

cancer biology↗

bioRxiv2018

CNApp: a web-based tool for integrative analysis of genomic copy number alterations in cancer

Somatic copy number alterations (CNAs) are a hallmark of cancer. Although CNA profiles have been established for most human tumor types, their precise role in tumorigenesis as well as their clinical and therapeutic relevance remain largely unclear. Thus, computational and statistical approaches are required to thoroughly define the interplay between CNAs and tumor phenotypes. Here we developed CNApp, a user-friendly web tool that offers sample- and cohort-level computational analyses, allowing a comprehensive and integrative exploration of CNAs with clinical and molecular variables. By using purity-corrected segmented data from multiple genomic platforms, CNApp generates genome-wide profiles, computes CNA scores for broad, focal and global CNA burdens, and uses machine learning-based predictions to classify samples. We applied CNApp to a pan-cancer dataset of 10,635 genomes from TCGA showing that CNA patterns classify cancer types according to their tissue-of-origin, and that broad and focal CNA scores positively correlate in samples with low amounts of whole-chromosome and chromosomal arm-level imbalances. Moreover, using the hepatocellular carcinoma cohort from the TCGA repository, we demonstrate the reliability of the tool in identifying recurrent CNAs, confirming previous results. Finally, we establish machine learning-based models to predict colon cancer molecular subtypes and microsatellite instability based on broad CNA scores and specific genomic imbalances. In summary, CNApp facilitates data-driven research and provides a unique framework for the first time to comprehensively assess CNAs and perform integrative analyses that enable the identification of relevant clinical implications. CNApp is hosted at http://cnapp.bsc.es.

genomics↗